Accelerometer-based physical activity patterns and correlates of depressive symptoms

Xia Li, Patricia M. Kearney, Anthony P. Fitzgerald

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Background: A number of observational and intervention studies have investigated the relationship between physical activity and mental health; however, few studies evaluate the association between physical activity and depression in a population sample by using minute by minute data over one week from accelerometer. The purpose of this study is to explore the different physical activity patterns and the relationships between these patterns and depression symptoms based on minute by minute accelerometer assessed data. Methods: Data from the Mitchelstown cohort study were used. Taking consider of non-wear time and background information missing, 375 participants were included in this study. They all completed questionnaires and wore accelerometers for seven consecutive days. Questionnaire provided background information and Center for Epidemiological Studies Depression Scale (CES-D) score measurements, accelerometer output provided minute by minute physical activity data. Bivariate smoothing method was used to explore the interaction effect of depression score and other continuous background covariates to CES-D, multiple regression analysis was used to get the relationship between CES-D score and physical activity level. Results: Within Day Physical activity profile analysis showed that after 11:00 pm and before around 7:00 am, participants in moderate and moderate to severe depression groups are much active than the other two groups, but during the other day time, moderate to severe group is less active than the others. There were strong contrasts between depression groups regarding time-of day of peak per minute activity. Daily activity gets progressively lower for moderate to severe group since between 7 am and 8 am, and the cumulative activity is the lowest among these four groups. Bivariate relationship analysis also showed there were difference between male and female, different depression groups participants.

Original languageEnglish
Title of host publicationHealth Information Science - 7th International Conference, HIS 2018, Proceedings
EditorsRui Zhou, Siuly Siuly, Hua Wang, Zhisheng Huang, Ickjai Lee, Wei Xiang
PublisherSpringer Verlag
Pages37-47
Number of pages11
ISBN (Print)9783030010775
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event7th International Conference on Health Information Science, HIS 2018 - Cairns, QLD, Australia
Duration: 5 Oct 20187 Oct 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11148 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Health Information Science, HIS 2018
Country/TerritoryAustralia
CityCairns, QLD
Period5/10/187/10/18

Keywords

  • Accelerometer
  • Bivariate smoothing
  • Depression
  • Physical activity
  • Tri-axial

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